code: def image_preprocess(img_path, re_shape):
      img = cv2.imread(img_path)
      img = cv2.resize(
          img, (re_shape, re_shape), interpolation=cv2.INTER_LANCZOS4
      )
      img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
      img = np.transpose(img, [2, 0, 1]) / 255
      img = np.expand_dims(img, 0)
      img_mean = np.array([0.485, 0.456, 0.406]).reshape((3, 1, 1))
      img_std = np.array([0.229, 0.224, 0.225]).reshape((3, 1, 1))
      img -= img_mean
      img /= img_std
      return img.astype(np.float32)
  
file_path: PaddleDetection/deploy/third_engine/demo_openvino/python/openvino_benchmark.py
imports: import cv2
  import numpy
  import time
  import argparse
  from scipy.special import softmax
  from openvino.runtime import Core
label_desc: Use image node_id 1 for calling a global function with example usage: image_preprocess(img_path, re_shape) and returns: img